Patterns of multiple congenital anomalies in the National Birth Defect Prevention Study: Challenges and insights

Surveillance of multiple congenital anomalies; searching for new associations

Many human teratogens are associated with a spectrum of congenital anomalies rather than a single defect, and therefore the identification of congenital anomalies occurring together more frequently than expected may improve the detection of teratogens. Thirty-two EUROCAT congenital anomaly registries covering 6,599,765 births provided 123,566 cases with one or more major congenital anomalies (excluding chromosomal and genetic syndromes) for the birth years 2008-2016. The EUROCAT multiple congenital anomaly algorithm identified 8804 cases with two or more major congenital anomalies in different organ systems, that were not recognized as part of a syndrome or sequence. For each pair of anomalies, the odds of a case having both anomalies relative to having only one anomaly was calculated and the p value was estimated using a two-sided Fisher's exact test. The Benjamini-Hochberg procedure adjusted p values to control the false discovery rate and pairs of anomalies with adjusted p values < 0.05 were identified. A total of 1386 combinations of two anomalies were analyzed. Out of the 31 statistically significant positive associations identified, 20 were found to be known associations or sequences already described in the literature and 11 were considered "potential new associations" by the EUROCAT Coding and Classification Committee. After a review of the literature and a detailed examination of the individual cases with the anomaly pairs, six pairs remained classified as new associations. In summary, systematically searching for congenital anomalies occurring together more frequently than expected using the EUROCAT database is worthwhile and has identified six new associations that merit further investigation.

Updated EUROCAT guidelines for classification of cases with congenital anomalies

BACKGROUND

Precise and correct classification of congenital anomalies is important in epidemiological studies, not only to classify according to etiology but also to group similar congenital anomalies together, to create homogeneous subgroups for surveillance and research. This paper presents the updated EUROCAT (European surveillance of congenital anomalies) subgroups of congenital anomalies and the updated multiple congenital anomaly (MCA) algorithm and provides the underlying arguments for the revisions.

METHODS

The EUROCAT methodology is described. In addition, we show how we validated the revised EUROCAT subgroups and MCA algorithm, which are both based on the International Classification of Diseases (ICD10/ICD9) codes.

RESULTS

The updated EUROCAT subgroups and the updated MCA algorithm are described in detail and the updated version is compared to the previous versions.

CONCLUSION

The EUROCAT subgroups and MCA algorithm provide a standardized and clear methodology for congenital anomaly research and epidemiological surveillance of congenital anomalies in order to facilitate the identification of teratogenic exposures and to assess the impact of primary prevention and prenatal screening policies. The EUROCAT subgroups and MCA algorithm are made freely available for other researchers via the EUROCAT Database Management Software.

Patterns of co-occurring birth defects in children with anotia and microtia

Many infants with anotia or microtia (A/M) have co-occurring birth defects, although few receive syndromic diagnoses in the perinatal period. Evaluation of co-occurring birth defects in children with A/M could identify patterns indicative of undiagnosed/unrecognized syndromes. We obtained information on co-occurring birth defects among infants with A/M for delivery years 1999-2014 from the Texas Birth Defects Registry. We calculated observed-to-expected ratios (OER) to identify birth defect combinations that occurred more often than expected by chance. We excluded children diagnosed with genetic or chromosomal syndromes from analyses. Birth defects and syndromes/associations diagnosed ≤1 year of age were considered. We identified 1310 infants with non-syndromic A/M, of whom 38% (N = 492) were diagnosed with co-occurring major defects. Top combinations included: hydrocephalus, ventricular septal defect, and spinal anomalies (OER 58.4); microphthalmia and anomalies of the aorta (OER 55.4); and cleft lip with or without cleft palate and rib or sternum anomalies (OER 32.8). Some combinations observed in our study may represent undiagnosed/atypical presentations of known A/M associations or syndromes, or novel syndromes yet to be described in the literature. Careful evaluation of infants with multiple birth defects including A/M is warranted to identify individuals with potential genetic or chromosomal syndromes.

Identifying syndromes in studies of structural birth defects: Guidance on classification and evaluation of potential impact

Structural birth defects that occur in infants with syndromes may be etiologically distinct from those that occur in infants in whom there is not a recognized pattern of malformations; however, population-based registries often lack the resources to classify syndromic status via case reviews. We developed criteria to systematically identify infants with suspected syndromes, grouped by syndrome type and level of effort required for syndrome classification (e.g., text search). We applied this algorithm to the Texas Birth Defects Registry (TBDR) to describe the proportion of infants with syndromes delivered during 1999-2014. We also developed a bias analysis tool to estimate the potential percent bias resulting from including infants with syndromes in studies of risk factors. Among 207,880 cases with birth defects in the TBDR, 15% had suspected syndromes and 85% were assumed to be nonsyndromic, with a range across defect types from 28.5% (atrioventricular septal defects) to 98.9% (pyloric stenosis). Across hypothetical scenarios varying expected parameters (e.g., nonsyndromic proportion), the inclusion of syndromic cases in analyses resulted in up to 50.0% bias in prevalence ratios. In summary, we present a framework for identifying infants with syndromic conditions; implementation might harmonize syndromic classification across registries and reduce bias in association estimates.